Supply and demand balance regulation and control optimization method considering source network load storage flexibility resources

Abstract

The invention provides a supply and demand balance regulation and control optimization method considering source network load storage flexibility resources, and belongs to the technical field of source network load storage resource optimization regulation and control. The problem that the optimization effect is not ideal due to the fact that loss caused by insufficient flexibility in a power system in existing research is not reasonably quantified is solved. According to the method, the whole-life-cycle carbon emission of the flexible resources of the source network load storage whole chain is considered, and a carbon transaction mechanism is designed to promote low-carbon operation of the flexible resources; measuring wind curtailment and light curtailment risk loss caused by insufficient flexibility through a CVaR method; and a multi-target flexibility resource balance optimization regulation and control model is constructed, and safe and low-carbon operation of the power system is ensured.

Description

Technical Field

[0001] The present invention provides a supply and demand balance control optimization method considering the source, grid, load and storage flexibility resources, belonging to the technical field of source, grid, load and storage resource optimization control. Background Art

[0002] In order to make full use of renewable energy power generation and reduce the occurrence of wind and solar power abandonment, the concept of flexibility resources has been proposed in the process of improving the regulation capacity of the power system. In the future, the demand for flexibility resources in the power system will increase significantly. However, ensuring the real-time balance of supply and demand of flexibility resources in the power system is a difficult problem, which brings challenges to the safe and stable operation of the power grid, and also puts higher requirements on the flexibility of the power system. Therefore, the coordinated development of flexibility resources is an effective way to resolve the contradiction between flexibility supply and demand. In order to improve the flexibility of the power system, it is necessary to connect flexibility resources including energy storage systems, pumped storage systems and demand response resources to the power system. By deeply exploring the potential of multiple types of potential flexibility resources in the source, load, storage and other links, multiple types of flexibility resources can be economically and efficiently configured to meet the development needs of renewable energy.

[0003] There have been many studies on the optimization of flexible resource operation. Some scholars have proposed setting up multiple operation scenarios for different priority targets to stimulate the operational flexibility of distributed energy systems. Some scholars have considered flexibility characteristics such as spatiotemporal coupling and proposed an operation optimization method based on regional scheduling total budget and carbon emission constraints. Some scholars have proposed a mixed integer nonlinear optimization model to achieve a balance between energy planning supply and actual output in response to uncertainties such as load forecasting, weather changes, and equipment failures. Some scholars have proposed a method based on comprehensive flexible regions to characterize and measure comprehensive flexibility, while considering the time coupling constraints of distributed multi-energy systems, and incorporating decoupled comprehensive flexible regions into the multi-period economic dispatch of centralized energy systems.

[0004] At present, the research on the flexibility of power system is mostly focused on supply and demand balance, planning and configuration, and dispatching and operation, while there are few studies on the economic cost and risk cost of flexibility. Some scholars consider the flexibility price in the objective function to reasonably compensate the equipment that provides flexibility in the system. Some scholars propose that the transmission network operator obtains revenue by selling flexibility to the distribution network operator and compensates the flexibility cost of the transmission network operator. Some scholars propose a tradable flexibility resource certificate, which is purchased by renewable energy generators, otherwise they will not be able to participate in the energy market, which to a certain extent alleviates the problems of new power systems such as insufficient flexibility. Some scholars measure the degree of freedom of individual energy flexibility by designing flexibility scores. The above-mentioned research on the economic cost and price of flexibility is mostly reflected in the level of compensating flexibility value, but there is no further in-depth research on the risk loss caused by insufficient system flexibility.

[0005] In summary, new energy installations will penetrate the power grid power generation system at a high rate, but the output of new energy is highly volatile and uncertain, and its grid-connected operation brings great challenges to the power system. Many studies have confirmed that flexibility resources play an important role in the high-generation grid-connected new energy in the power system, which can effectively reduce the system operation cost and reduce carbon emissions. In existing studies, it was found that insufficient flexibility has a great impact on the safe and stable operation of the power system, but the losses caused by insufficient flexibility in the system have not been reasonably quantified. Summary of the invention

[0006] In order to solve the above technical problems, the present invention proposes a supply and demand balance control optimization method taking into account the flexibility resources of source, grid, load and storage.

[0007] The technical solution adopted by the present invention is: a supply and demand balance control optimization method considering the source, network, load and storage flexibility resources, comprising the following steps: 1) Construct a carbon emission calculation model based on the life cycle energy chain to calculate the greenhouse gas emissions directly generated by power system activities or input materials; 2) Based on the difference between the total carbon emissions of the life cycle energy chain and the carbon quota, the carbon trading principle and mathematical model are constructed to calculate the amount of CO2 actually involved in carbon trading for each flexible resource; 3) Set the loss index for insufficient upward and downward adjustment of flexible resources, and use the CVaR method to quantitatively analyze the wind and solar power abandonment losses when the flexible resources are insufficiently adjusted upward and downward; 4) Construct a risk model for insufficient flexibility and calculate the total CVaR value of power system load shedding and wind and solar power abandonment through Monte Carlo simulation method; 5) Construct a flexibility resource cost function to enable safe and low-carbon operation of the power system.

[0008] The carbon emission calculation model based on the life cycle energy chain constructed in step 1) calculates the CO2 emissions of the kth flexible resource over its entire life cycle The formula is as follows: ; ; Where: for t Moment k Carbon emissions of the flexible resource over its entire life cycle; and They are t At any time, the power system k Flexibility to meet both upward and downward resource demands; For the k The carbon emission coefficient of the flexible resource over its entire life cycle; and They are t Moment k Whether the flexibility resource participates in the upward and downward flexibility adjustment of the system is a 0-1 variable.

[0009] k =1 represents the flexibility transformation of thermal power units; k =2 represents gas turbine; k =3 represents a hydroelectric unit; k =4 represents electrochemical energy storage; k =5 represents pumped storage; k =6 represents load demand response; k =7 represents grid mutual assistance; when k =1, 2, 3, Represents the power of increasing the output of flexible resources, represents the power of reducing the output of flexible resources; when k =4, Represents the electrochemical energy storage power generation, Represents the electrochemical energy storage charging power; when k =5, represents the pumped storage power generation capacity, represents the pumped storage pumping power; k =6, The reduction of electricity load due to demand response on behalf of users, Increased electricity load due to demand response on behalf of customers; k =7, Represents the reduction of grid mutual aid power, It represents an increase in the mutual aid power of the power grid.

[0010] The carbon trading principle and mathematical model constructed in step 2) are based on the flexibility resource k After deducting the quota, the actual carbon emissions that are greater than the quota are included in the participatory carbon trading. The mathematical model is expressed as follows: ; ; Where: For the k The trading volume of various flexibility resources participating in the carbon market; For the k Carbon quotas for flexible resources; For the k The cost or benefit of a flexible resource participating in the carbon market When positive, it means k The benefits of this flexible resource participating in the carbon market are When negative, it meansk The cost of various flexibility resources participating in the carbon market; is the unit price of carbon trading; T is the flexibility resource life cycle; Δ T It is the length of a period in the life cycle of a flexibility resource.

[0011] The expressions of the flexibility resource upward and downward adjustment loss indicators set in step 3) are as follows: ; Where: and They are t Losses due to insufficient upward and downward adjustments of time flexibility resources; for t The unit cost of insufficient upward adjustment of momentary flexibility resources is the cost of load shedding losses; for t The time-of-day flexibility resource is reduced to less than the unit cost, that is, the loss cost of wind and solar power abandonment; for t The net load at all times adjusts demand upward; for t The net load at all times adjusts demand downward; and They are t The total upward and downward supply capacity of power system flexibility resources at any given moment; in: ; ; Where: L t,net for t Net load of power system at any moment; and They are t At any time, the power system k Flexibility to meet both upward and downward resource demands; and They are t Moment k Whether the flexibility resource participates in the upward and downward flexibility adjustment of the system is a 0-1 variable.

[0012] The flexibility shortage risk model constructed in step 4) uses the CVaR model to quantitatively analyze the risk cost when the flexibility resources are insufficiently adjusted upward or downward. The confidence level based on the deviation of the output of renewable energy reflects the uncertainty of renewable energy, and its deviation loss does not exceed the critical value. α The specific calculation formula of the probability is as follows: ; ; Where: α The output deviation loss of renewable energy power generation does not exceed the critical value; Prob ( ) is the probability function; , is the probability density function; At the confidence level β The CvaR of power system load loss and wind curtailment loss is calculated as follows: ; ; Where: is the confidence level β Down t Conditional risk value of system load shedding during the period; is the confidence level β Down t The conditional value at risk of system wind curtailment during the period; ; Through the Monte Carlo simulation method, random , Variable M , N discrete points are used as sample points to calculate the total loss CVaR value of the power system load shedding and wind and solar power abandonment. The specific formula is as follows: ; Where: for t The estimated value of the probability density function of the loss of flexibility in adjusting up and down the time period; for t The estimated value of the probability density function of the loss of flexibility in the period of adjustment upward; The estimated value of the probability density function of the loss of insufficient flexibility in period t.

[0013] The expression of the flexibility resource cost function constructed in step 5) is as follows: ; The constraints are as follows: ; Where: C sys is the total cost of power system flexibility resources; is the carbon emission cost of flexibility resources; for t Time period k The operating costs of the flexibility transformation of thermal power and gas turbine flexibility resources; for t Time period kThe operating costs of various flexibility resources such as hydropower, electrochemical energy storage, pumped storage, load demand response and grid mutual assistance; is the confidence level β Down t Conditional risk value of system load shedding during the period; is the confidence level β Down t The conditional value at risk of system wind curtailment during the period; for t Transformation of thermal power units with time flexibility i The power generation capacity; , Electrochemical energy storage t Charging and discharging power during time period; for t Pumped storage power generation capacity during the period; for t Pumping power of pumped storage during the period; for t The load power of a time period can be shifted to other time periods; for t The load power can be reduced during the period; for t The time period can be shifted to the load power of this time period; for t Load shedding power during the period; For new energy t Power abandonment during time period; N i Modify the number of thermal power units for flexibility.

[0014] ; ; Where: a k For the k The quadratic unit cost coefficient for the flexibility transformation of thermal power units and gas turbines; b k For the k The first-time unit cost coefficient of the flexibility resource; c k For the k The constant term fixed cost coefficient of the flexibility resource.

[0015] The power generation constraints of the flexible transformation thermal power units include: the power of the flexible transformation generating units, the shortest start and stop time, the unit operation status at a certain moment, and the start and stop status constraints of the unit at a certain moment; The load demand response constraints include: load shifting constraints and load reduction constraints, where the load shifting constraints include: the power of loads that can be shifted from a certain period to other periods, the power of loads that can be shifted from a certain period to this period, and the sign constraints of shifting loads; The constraints on load reduction include the power constraints on load reduction in a certain period of time; Electrochemical energy storage constraints include: allowable amount of electrochemical energy storage, charge and discharge power of electrochemical energy storage in a certain period of time, and charge and discharge state constraints; Pumped storage constraints include: pumped storage power generation, pumping power and power generation, pumping state constraints and pumping reservoir storage capacity constraints in a certain period of time.

[0016] Compared with the prior art, the present invention has the following beneficial effects: the present invention takes into account the carbon emissions of flexible resources in the entire chain of source, grid, load and storage throughout their life cycle, designs a carbon trading mechanism to promote the low-carbon operation of flexible resources; measures the risk loss of wind and solar power abandonment caused by insufficient flexibility through the CVaR method; and constructs a multi-objective flexibility resource balance optimization and control model to ensure safe and low-carbon operation of the power system.

[0017] In addition, existing research generally relies on multiple inequality constraints when considering economy and low carbon. However, the multi-objective flexibility resource balance optimization and control model proposed in the present invention integrates the carbon trading mechanism, which can simultaneously stimulate the contribution of flexibility resources in economy and low carbon.

[0018] Furthermore, the present invention quantifies the risk cost caused by insufficient flexibility from the perspective of safe and stable operation of the power system, effectively reducing the losses caused by load shedding and wind and solar power abandonment. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The present invention will be further described below in conjunction with the accompanying drawings: Figure 1 The figure is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0020] like Figure 1 As shown, the present invention provides a supply and demand balance control optimization method considering the source, network, load and storage flexibility resources, including the following steps: 1) Construct a carbon emission calculation model based on the life cycle energy chain to calculate the greenhouse gas emissions directly generated by power system activities or input materials; 2) Based on the difference between the total carbon emissions of the life cycle energy chain and the carbon quota, the carbon trading principle and mathematical model are constructed to calculate the amount of CO2 actually involved in carbon trading for each flexible resource; 3) Set the loss index for insufficient upward and downward adjustment of flexible resources, and use the CVaR method to quantitatively analyze the wind and solar power abandonment losses when the flexible resources are insufficiently adjusted upward and downward; 4) Construct a risk model for insufficient flexibility and calculate the total CVaR value of power system load shedding and wind and solar power abandonment through Monte Carlo simulation method; 5) Design the flexibility resource cost function, and based on the principle that the total supply of flexibility resources in the power system is equal to the total demand (net load), design the constraints of the multi-objective flexibility resource balance optimization control model. Thus, a multi-objective flexibility resource balance optimization control model is obtained, which enables the safe and low-carbon operation of the power system.

[0021] The carbon emission calculation model constructed in step 1) uses the life cycle source-grid-load-storage carbon emission analysis method to calculate the greenhouse gas emissions directly generated by power system activities or input materials, taking into account the associated effects of power system operation or material-related transformation. The life cycle source-grid-load-storage carbon emission measurement scope is from source to grid to load to storage, excluding the transmission and distribution of secondary energy.

[0022] In order to reflect the total carbon emissions of the source-grid-load-storage chain of the flexible resource, the sum of the carbon emissions of the corresponding operating equipment in each stage is calculated based on the flexible resource life cycle. : (1); (2); Where: for t Moment k Carbon emissions of the flexible resource over its entire life cycle; and They are t At any time, the power system k Flexibility to meet both upward and downward resource demands; For the k The carbon emission coefficient of the flexible resource over its entire life cycle; and They are t Moment k Whether the flexibility resource participates in the upward and downward flexibility adjustment of the system is a 0-1 variable.

[0023] in, k =1 represents the flexibility transformation of thermal power units; k =2 represents gas turbine; k =3 represents a hydroelectric unit; k =4 represents electrochemical energy storage; k =5 represents pumped storage; k =6 represents load demand response; k =7 represents grid mutual assistance.

[0024] whenk =1, 2, 3, Represents the power of increasing the output of flexible resources, represents the power of reducing the output of flexible resources; when k =4, Represents the electrochemical energy storage power generation, Represents the electrochemical energy storage charging power; when k =5, represents the pumped storage power generation capacity, represents the pumped storage pumping power; k =6, The reduction of electricity load due to demand response on behalf of users, Increased electricity load due to demand response on behalf of customers; k =7, Represents the reduction of grid mutual aid power, It represents an increase in the mutual aid power of the power grid.

[0025] make: (3); Where: P k,t For the k Flexibility Resources t The power of the moment.

[0026] The carbon trading principle and mathematical model constructed in step 2) are based on the flexibility resource k After deducting the quota, the actual carbon emissions that are greater than the quota will be included in the carbon trading. The mathematical model is expressed as follows: (4); (5); Where: For the k The trading volume of various flexibility resources participating in the carbon market; For the k Carbon quotas for flexible resources; For the k The cost or benefit of a flexible resource participating in the carbon market When positive, it means k The benefits of this flexible resource participating in the carbon market are When negative, it means k The cost of various flexibility resources participating in the carbon market; is the unit price of carbon trading; T is the flexibility resource life cycle; Δ T It is the length of a period in the life cycle of a flexibility resource.

[0027] The calculation process of the flexibility resource upward and downward adjustment loss indicators set in step 3) is as follows: set up: (6); Where: L t,net for t Net load of power system at any moment; L t for t User load at any moment; for t Wind power at each moment; for t Photovoltaic power at all times; P k,t For the k Flexibility Resources t The power of the moment.

[0028] set up: (7); (8); but: (9); Where: for t The net load at all times adjusts demand upward; for t The net load at all times adjusts demand downward; and They are t The total upward and downward supply capacity of power system flexibility resources at any given moment; and They are t Losses due to insufficient upward and downward adjustments of time flexibility resources; for t The unit cost of insufficient upward adjustment of momentary flexibility resources, i.e. the cost of load shedding loss, can be calculated and analyzed with reference to the interruptible electricity price; for t The unit cost of the momentary flexibility resource reduction is insufficient, that is, the loss cost of wind and solar power abandonment, which can be calculated and analyzed based on the price of wind power and photovoltaic power; K Types of flexibility resources.

[0029] When there is insufficient upward flexibility, the power system will face the risk of load shedding; when there is insufficient downward flexibility, the power system will face the risk of wind and solar power abandonment. Therefore, a risk model of insufficient flexibility is constructed, and the penalty cost of insufficient flexibility resources is introduced. Through typical day operation simulation, iterative feedback is performed based on whether the flexibility supply and demand balance constraints are met to achieve the optimal configuration of flexibility resources.

[0030] The present invention adopts the CVaR model to quantitatively analyze the risk cost when the flexibility resources are adjusted upward or downward, and reflects the uncertainty of new energy based on the confidence level of the new energy power generation output deviation. The loss of new energy power generation output deviation does not exceed the critical value. α The specific calculation formula of the probability is as follows: (10); (11); Where: α The output deviation loss of renewable energy power generation does not exceed the critical value; Prob ( ) is the probability that the loss of flexible resources will not exceed the critical value if the upward or downward adjustment is insufficient; its probability density function , It is difficult to calculate, but the Monte Carlo simulation method can be used to select random variables. M , N discrete points as sample points.

[0031] The present invention is at a confidence level β The CvaR of load shedding and wind abandonment losses in the power system is calculated as follows: (12); (13); Where: is the confidence level β Down t Conditional risk value of system load shedding (lack of upward flexibility) during the period; is the confidence level β Down t The conditional value at risk of system wind curtailment (lack of downward flexibility) during the period; .

[0032] The present invention uses the Monte Carlo simulation method to select random , Variable M , N discrete points are used as sample points to calculate the total loss CVaR value of the power system load shedding and wind and solar power abandonment. The specific formula is as follows: (14); Where: for t The estimated value of the probability density function of the loss of flexibility in adjusting up and down the time period; for t The estimated value of the probability density function of the loss of flexibility in the period of adjustment upward; for tThe probability density function estimate of the loss of flexibility due to period downgrade.

[0033] The expression of the flexibility resource cost function designed in step 5) is as follows: (15); (16); Where: for t Time period k The operating costs of the flexibility resources (here representing the flexibility transformation of thermal power and gas turbines); for t Time period k The operating costs of various flexibility resources (here representing hydropower, electrochemical energy storage, pumped storage, load demand response and grid mutual assistance); a k The quadratic unit cost coefficient for the k-th flexibility modification of thermal power units and gas turbines; b k is the first-order unit cost coefficient of the k-th flexibility resource; c k is the constant fixed cost coefficient of the kth flexibility resource.

[0034] The expression of the multi-objective flexibility resource balance optimization control model constructed in step 5) is as follows: (17); The constraint condition of the above objective function is that the total supply of flexible resources in the power system is equal to the total demand (net load), as shown in the following formula: (18); Where: C sys is the total cost of power system flexibility resources; is the carbon emission cost of flexibility resources; for t Transformation of thermal power units with time flexibility i The power generation capacity; , Electrochemical energy storage t Charging and discharging power during time period; for t Pumped storage power generation capacity during the period; for t Pumping power of pumped storage during the period; for t The load power of a time period can be shifted to other time periods; for t The load power can be reduced during the period; fort The time period can be shifted to the load power of this time period; for t Load shedding power during the period; For new energy t Power abandonment during time period; N i Modify the number of thermal power units for flexibility.

[0035] The specific expressions of each constraint are as follows.

[0036] a. The power generation constraints of the thermal power units for flexibility transformation are as follows: (19); (20); (twenty one); (twenty two); Where: Retrofitting thermal power plants for flexibility i Minimum power generation capacity; Retrofitting thermal power plants for flexibility i Maximum power generation capacity; Retrofitting thermal power plants for flexibility i The climbing rate of the rise; is the descending ramp rate of the thermal power unit; for t -1 hour traditional thermal power unit tro Startup time; , Conventional thermal power units tro The shortest start and stop time; for t Traditional thermal power units tro The operating status of for t -1 hour traditional thermal power unit tro downtime; , They are t Traditional thermal power units tro The start and stop status is a 0-1 variable.

[0037] b. Load demand response constraints are as follows: The load-side flexibility supply is mainly used to provide a certain proportion of demand response. It can be divided into shiftable load and curtailable load. The shiftable load means that the total load on the user side remains unchanged and only the power consumption time is changed, while the curtailable load means that the load is directly interrupted without shifting.

[0038] c. The constraints of the translatable load are as follows: (twenty three); (twenty four); (25); Where: , They are t The time period can be shifted to other time periods with maximum and minimum load power; , The time periods t The maximum and minimum values ​​of load power can be transferred from other time periods; , They are t The flag that indicates whether the load is shifted during the period, which is a 0-1 variable.

[0039] d. The expression for load reduction is as follows: (26); Where: for t The maximum value of load that can be reduced during a period; for t The flag that indicates the load can be reduced during the period, which is a 0-1 variable.

[0040] e. The constraints of electrochemical energy storage are as follows: (27); (28); (29); (30); Where: E t for t The amount of energy stored in electrochemical energy storage during a period of time; E max , E min for t Maximum and minimum values ​​of electrochemical energy storage capacity during a period of time; , are the charging and discharging efficiency of electrochemical energy storage, respectively; , They are t Maximum power of electrochemical energy storage charging and discharging during a certain period of time; , They are t Minimum power for charging and discharging electrochemical energy storage during a certain period of time; , They are tTime period electrochemical energy storage charging and discharging power; p k,t , l k,t They are t The charging and discharging state of electrochemical energy storage during the time period is a 0-1 variable; Δ t The time interval for scheduling electrochemical energy storage.

[0041] f. Pumped storage constraints are as follows: (31); (32); (33); (34); Where: , They are T 'Period pumped storage power generation, pumping power; , They are t The state of pumped storage power generation and pumping at each moment, which is a 0-1 variable; , They are the maximum and minimum power generation of pumped storage respectively; , They are the maximum and minimum pumping power of pumped storage respectively; for t Periodic pumped storage to store energy in reservoirs; , The pumping and power generation efficiency of pumped storage units; , They are the maximum and minimum storage capacities of the pumped storage reservoir respectively.

[0042] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A supply and demand balance control optimization method considering the flexibility of source, grid, load and storage resources, characterized by: The following steps are involved: 1) Construct a carbon emission calculation model based on the life cycle energy chain to calculate the greenhouse gas emissions directly generated by power system activities or input materials; 2) Based on the difference between the total carbon emissions of the life cycle energy chain and the carbon quota, the carbon trading principle and mathematical model are constructed to calculate the amount of CO2 actually involved in carbon trading for each flexible resource; 3) Set the loss index for insufficient upward and downward adjustment of flexible resources, and use the CVaR method to quantitatively analyze the wind and solar power abandonment losses when the flexible resources are insufficiently adjusted upward and downward; 4) Construct a risk model for insufficient flexibility and calculate the total CVaR value of power system load shedding and wind and solar power abandonment through Monte Carlo simulation method; 5) Construct a flexibility resource cost function to enable safe and low-carbon operation of the power system.

2. A supply and demand balance control optimization method considering the flexibility of source, grid, load and storage resources according to claim 1, characterized in that: The carbon emission calculation model based on the life cycle energy chain constructed in step 1) calculates the CO2 emissions of the kth flexible resource over its entire life cycle The formula is as follows: ； ； Where: for t Moment k Carbon emissions of the flexible resource over its entire life cycle; and They are t At any time, the power system k Flexibility to meet both upward and downward resource demands; For the k The carbon emission coefficient of the flexible resource over its entire life cycle; and They are t Moment k Whether the flexibility resource participates in the upward and downward flexibility adjustment of the system is a 0-1 variable.

3. A supply and demand balance control optimization method considering the flexibility of source, grid, load and storage resources according to claim 2, characterized in that: k =1 represents the flexibility transformation of thermal power units; k =2 represents gas turbine; k =3 represents a hydroelectric unit; k =4 represents electrochemical energy storage; k =5 represents pumped storage; k =6 represents load demand response; k =7 represents grid mutual assistance; when k =1, 2, 3, Represents the power of increasing the output of flexible resources, represents the power of reducing the output of flexible resources; when k =4, Represents the electrochemical energy storage power generation, Represents the electrochemical energy storage charging power; when k =5, represents the pumped storage power generation capacity, represents the pumped storage pumping power; k =6, The reduction of electricity load due to demand response on behalf of users, Increased electricity load due to demand response on behalf of customers; k =7, Represents the reduction of grid mutual aid power, It represents an increase in the mutual aid power of the power grid.

4. The supply and demand balance control optimization method considering the source, grid, load and storage flexibility resources according to claim 3 is characterized by: The carbon trading principle and mathematical model constructed in step 2) are based on the flexibility resource k After deducting the quota, the actual carbon emissions that are greater than the quota are included in the participatory carbon trading. The mathematical model is expressed as follows: ； ； Where: For the k The trading volume of various flexibility resources participating in the carbon market; For the k Carbon quotas for flexible resources; For the k The cost or benefit of a flexible resource participating in the carbon market When positive, it means k The benefits of this flexible resource participating in the carbon market are When negative, it means k The cost of various flexibility resources participating in the carbon market; is the unit price of carbon trading; T is the flexibility resource life cycle; Δ T It is the length of a period in the life cycle of a flexibility resource.

5. The supply and demand balance control optimization method considering the source, grid, load and storage flexibility resources according to claim 4 is characterized by: The expressions of the flexibility resource upward and downward adjustment loss indicators set in step 3) are as follows: ； Where: and They are t Losses due to insufficient upward and downward adjustments of time flexibility resources; for t The unit cost of insufficient upward adjustment of momentary flexibility resources is the cost of load shedding losses; for t The time-of-day flexibility resource is reduced to less than the unit cost, that is, the loss cost of wind and solar power abandonment; for t The net load at all times adjusts demand upward; for t The net load at all times adjusts demand downward; and They are t The total upward and downward supply capacity of power system flexibility resources at any given moment; in: ； ； Where: L t,net for t Net load of power system at any moment; and They are t At any time, the power system k Flexibility to meet both upward and downward resource demands; and They are t Moment k Whether the flexibility resource participates in the upward and downward flexibility adjustment of the system is a 0-1 variable.

6. A supply and demand balance control optimization method considering the flexibility of source, grid, load and storage resources according to claim 5, characterized in that: The flexibility shortage risk model constructed in step 4) uses the CVaR model to quantitatively analyze the risk cost when the flexibility resources are insufficiently adjusted upward or downward. The confidence level based on the deviation of the output of renewable energy reflects the uncertainty of renewable energy, and its deviation loss does not exceed the critical value. α The specific calculation formula of the probability is as follows: ； ； Where: α The output deviation loss of renewable energy power generation does not exceed the critical value; Prob ( ) is the probability function; , is the probability density function; At the confidence level β The CvaR of power system load loss and wind curtailment loss is calculated as follows: ； ； Where: is the confidence level β Down t Conditional risk value of system load shedding during the period; is the confidence level β Down t The conditional value at risk of system wind curtailment during the period; ; Through the Monte Carlo simulation method, random , Variable M , N discrete points are used as sample points to calculate the total loss CVaR value of the power system load shedding and wind and solar power abandonment. The specific formula is as follows: ； Where: for t The estimated value of the probability density function of the loss of flexibility in adjusting up and down the time period; for t The estimated value of the probability density function of the loss of flexibility in the period of adjustment upward; The estimated value of the probability density function of the loss of insufficient flexibility in period t.

7. The supply and demand balance control optimization method considering the flexibility of source, grid, load and storage resources according to claim 3 is characterized by: The expression of the flexibility resource cost function constructed in step 5) is as follows: ； The constraints are as follows: ； Where: C sys is the total cost of power system flexibility resources; The carbon emission cost of flexibility resources; for t Time period k The operating costs of the flexibility transformation of thermal power and gas turbine flexibility resources; for t Time period k The operating costs of various flexibility resources such as hydropower, electrochemical energy storage, pumped storage, load demand response and grid mutual assistance; is the confidence level β Down t Conditional risk value of system load shedding during the period; is the confidence level β Down t The conditional value at risk of system wind curtailment during the period; for t Transformation of thermal power units with time flexibility i The power generation capacity; , Electrochemical energy storage t Charging and discharging power during time period; for t Pumped storage power generation capacity during the period; for t Pumping power of pumped storage during the period; for t The load power of a time period can be shifted to other time periods; for t The load power can be reduced during the period; for t The time period can be shifted to the load power of this time period; for t Load shedding power during the period; For new energy t Power abandonment during time period; N i Modify the number of thermal power units for flexibility.

8. The supply and demand balance control optimization method considering the flexibility of source, grid, load and storage resources according to claim 7 is characterized by: ； ； Where: a k For the k The quadratic unit cost coefficient for the flexibility transformation of thermal power units and gas turbines; b k For the k The first-time unit cost coefficient of the flexibility resource; c k For the k The constant term fixed cost coefficient of the flexibility resource.

9. The supply and demand balance control optimization method considering the source, grid, load and storage flexibility resources according to claim 7 is characterized by: The power generation constraints of the flexible transformation thermal power units include: the power of the flexible transformation generating units, the shortest start and stop time, the unit operation status at a certain moment, and the start and stop status constraints of the unit at a certain moment; The load demand response constraints include: load shifting constraints and load reduction constraints, where the load shifting constraints include: the power of loads that can be shifted from a certain period to other periods, the power of loads that can be shifted from a certain period to this period, and the sign constraints of shifting loads; The constraints on load reduction include the power constraints on load reduction in a certain period of time; Electrochemical energy storage constraints include: allowable amount of electrochemical energy storage, charge and discharge power of electrochemical energy storage in a certain period of time, and charge and discharge state constraints; Pumped storage constraints include: pumped storage power generation, pumping power and power generation, pumping state constraints and pumping reservoir storage capacity constraints in a certain period of time.

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